Overview

Dataset statistics

Number of variables48
Number of observations4272
Missing cells100400
Missing cells (%)49.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory384.0 B

Variable types

Numeric7
Unsupported2
Categorical39

Alerts

uf_de_nascimento_do_paciente has constant value ""Constant
uf_de_residencia_do_paciente has constant value ""Constant
historia_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_2o_grau_apenas_1_caso has constant value ""Constant
historia_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_2o_grau_mais_de_1_caso has constant value ""Constant
qual_metodo_choice_diu has constant value ""Constant
qual_metodo_choice_camisinha has constant value ""Constant
qual_metodo_choice_outros has constant value ""Constant
qual_metodo_choice_nao_informou has constant value ""Constant
hormonioterapia has constant value ""Constant
radioterapia has constant value ""Constant
data_da_ultima_informacao_sobre_o_paciente has a high cardinality: 2131 distinct valuesHigh cardinality
data_da_cirurgia has a high cardinality: 1653 distinct valuesHigh cardinality
data_de_inicio_do_tratamento_quimioterapia has a high cardinality: 1766 distinct valuesHigh cardinality
data_de_inicio_da_radioterapia has a high cardinality: 1708 distinct valuesHigh cardinality
sexo is highly imbalanced (92.9%)Imbalance
ja_ficou_gravida is highly imbalanced (91.4%)Imbalance
historia_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_nao is highly imbalanced (99.2%)Imbalance
historia_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_1o_grau_apenas_1_caso is highly imbalanced (92.3%)Imbalance
historia_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_1o_grau_mais_de_1_caso is highly imbalanced (98.0%)Imbalance
qual_metodo_choice_pilula_anticoncepcional is highly imbalanced (99.7%)Imbalance
ja_fez_uso_de_drogas is highly imbalanced (94.2%)Imbalance
consumo_de_alcool is highly imbalanced (51.1%)Imbalance
grau_de_parentesco_de_familiar_com_cancer_choice_primeiro_pais_irmaos_filhos is highly imbalanced (85.4%)Imbalance
grau_de_parentesco_de_familiar_com_cancer_choice_segundo_avos_tios_e_netos is highly imbalanced (87.9%)Imbalance
grau_de_parentesco_de_familiar_com_cancer_choice_terceiro_bisavos_tio_avos_primos_sobrinhos is highly imbalanced (91.1%)Imbalance
tipo_de_terapia_anti_her2_neoadjuvante is highly imbalanced (96.6%)Imbalance
repeat_instrument has 4272 (100.0%) missing valuesMissing
repeat_instance has 4272 (100.0%) missing valuesMissing
escolaridade has 215 (5.0%) missing valuesMissing
idade_do_paciente_ao_primeiro_diagnostico has 180 (4.2%) missing valuesMissing
sexo has 147 (3.4%) missing valuesMissing
raca_declarada_biobanco has 4038 (94.5%) missing valuesMissing
uf_de_nascimento_do_paciente has 4270 (> 99.9%) missing valuesMissing
uf_de_residencia_do_paciente has 4270 (> 99.9%) missing valuesMissing
ja_ficou_gravida has 3259 (76.3%) missing valuesMissing
quantas_vezes_ficou_gravida has 4228 (99.0%) missing valuesMissing
numero_de_partos has 4270 (> 99.9%) missing valuesMissing
idade_na_primeira_gestacao has 3375 (79.0%) missing valuesMissing
abortou has 4220 (98.8%) missing valuesMissing
amamentou_na_primeira_gestacao has 3230 (75.6%) missing valuesMissing
por_quanto_tempo_amamentou has 3584 (83.9%) missing valuesMissing
idade_da_primeira_mentruacao has 3247 (76.0%) missing valuesMissing
faz_uso_de_metodos_contraceptivo has 4269 (99.9%) missing valuesMissing
ja_fez_uso_de_drogas has 4123 (96.5%) missing valuesMissing
atividade_fisica has 3967 (92.9%) missing valuesMissing
consumo_de_tabaco has 4060 (95.0%) missing valuesMissing
consumo_de_alcool has 4068 (95.2%) missing valuesMissing
possui_historico_familiar_de_cancer has 4082 (95.6%) missing valuesMissing
regime_de_tratamento has 1409 (33.0%) missing valuesMissing
hormonioterapia has 4269 (99.9%) missing valuesMissing
data_da_cirurgia has 2056 (48.1%) missing valuesMissing
tipo_de_terapia_anti_her2_neoadjuvante has 3138 (73.5%) missing valuesMissing
radioterapia has 1947 (45.6%) missing valuesMissing
data_de_inicio_do_tratamento_quimioterapia has 1450 (33.9%) missing valuesMissing
esquema_de_hormonioterapia has 4260 (99.7%) missing valuesMissing
data_do_inicio_hormonioterapia_adjuvante has 4270 (> 99.9%) missing valuesMissing
data_de_inicio_da_radioterapia has 1949 (45.6%) missing valuesMissing
data_da_ultima_informacao_sobre_o_paciente is uniformly distributedUniform
numero_de_partos is uniformly distributedUniform
data_da_cirurgia is uniformly distributedUniform
data_de_inicio_do_tratamento_quimioterapia is uniformly distributedUniform
data_do_inicio_hormonioterapia_adjuvante is uniformly distributedUniform
data_de_inicio_da_radioterapia is uniformly distributedUniform
record_id has unique valuesUnique
repeat_instrument is an unsupported type, check if it needs cleaning or further analysisUnsupported
repeat_instance is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-02-28 14:18:48.620080
Analysis finished2023-02-28 14:19:08.409659
Duration19.79 seconds
Software versionydata-profiling vv4.0.0
Download configurationconfig.json

Variables

record_id
Real number (ℝ)

Distinct4272
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48652.36
Minimum302
Maximum82240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-02-28T14:19:08.571301image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum302
5-th percentile13992.4
Q131013
median53394
Q365816.75
95-th percentile78668.25
Maximum82240
Range81938
Interquartile range (IQR)34803.75

Descriptive statistics

Standard deviation20659.52
Coefficient of variation (CV)0.4246355
Kurtosis-0.99374558
Mean48652.36
Median Absolute Deviation (MAD)16732
Skewness-0.29501895
Sum2.0784288 × 108
Variance4.2681575 × 108
MonotonicityStrictly increasing
2023-02-28T14:19:08.896214image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
302 1
 
< 0.1%
60912 1
 
< 0.1%
60757 1
 
< 0.1%
60774 1
 
< 0.1%
60777 1
 
< 0.1%
60799 1
 
< 0.1%
60815 1
 
< 0.1%
60825 1
 
< 0.1%
60826 1
 
< 0.1%
60840 1
 
< 0.1%
Other values (4262) 4262
99.8%
ValueCountFrequency (%)
302 1
< 0.1%
710 1
< 0.1%
752 1
< 0.1%
1367 1
< 0.1%
1589 1
< 0.1%
1705 1
< 0.1%
1843 1
< 0.1%
1873 1
< 0.1%
1898 1
< 0.1%
1960 1
< 0.1%
ValueCountFrequency (%)
82240 1
< 0.1%
82205 1
< 0.1%
82131 1
< 0.1%
82124 1
< 0.1%
82123 1
< 0.1%
82122 1
< 0.1%
82118 1
< 0.1%
82112 1
< 0.1%
82111 1
< 0.1%
82100 1
< 0.1%

repeat_instrument
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4272
Missing (%)100.0%
Memory size33.5 KiB

repeat_instance
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing4272
Missing (%)100.0%
Memory size33.5 KiB

escolaridade
Categorical

Distinct6
Distinct (%)0.1%
Missing215
Missing (%)5.0%
Memory size33.5 KiB
IGNORADA
2535 
ENSINO MÉDIO
488 
ENS. FUNDAMENTAL INCOMPLETO
445 
ENS. FUNDAMENTAL COMPLETO
357 
SUPERIOR
 
174

Length

Max length27
Median length8
Mean length12.089721
Min length8

Characters and Unicode

Total characters49048
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENS. FUNDAMENTAL INCOMPLETO
2nd rowENSINO MÉDIO
3rd rowENS. FUNDAMENTAL INCOMPLETO
4th rowENS. FUNDAMENTAL INCOMPLETO
5th rowENS. FUNDAMENTAL COMPLETO

Common Values

ValueCountFrequency (%)
IGNORADA 2535
59.3%
ENSINO MÉDIO 488
 
11.4%
ENS. FUNDAMENTAL INCOMPLETO 445
 
10.4%
ENS. FUNDAMENTAL COMPLETO 357
 
8.4%
SUPERIOR 174
 
4.1%
ANALFABETO 58
 
1.4%
(Missing) 215
 
5.0%

Length

2023-02-28T14:19:09.294729image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:09.622946image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
ignorada 2535
41.2%
ens 802
 
13.0%
fundamental 802
 
13.0%
ensino 488
 
7.9%
médio 488
 
7.9%
incompleto 445
 
7.2%
completo 357
 
5.8%
superior 174
 
2.8%
analfabeto 58
 
0.9%

Most occurring characters

ValueCountFrequency (%)
A 6848
14.0%
N 6420
13.1%
O 5347
10.9%
I 4130
8.4%
D 3825
 
7.8%
E 3126
 
6.4%
R 2883
 
5.9%
G 2535
 
5.2%
2092
 
4.3%
M 2092
 
4.3%
Other values (10) 9750
19.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 46154
94.1%
Space Separator 2092
 
4.3%
Other Punctuation 802
 
1.6%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 6848
14.8%
N 6420
13.9%
O 5347
11.6%
I 4130
8.9%
D 3825
8.3%
E 3126
6.8%
R 2883
 
6.2%
G 2535
 
5.5%
M 2092
 
4.5%
T 1662
 
3.6%
Other values (8) 7286
15.8%
Space Separator
ValueCountFrequency (%)
2092
100.0%
Other Punctuation
ValueCountFrequency (%)
. 802
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 46154
94.1%
Common 2894
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 6848
14.8%
N 6420
13.9%
O 5347
11.6%
I 4130
8.9%
D 3825
8.3%
E 3126
6.8%
R 2883
 
6.2%
G 2535
 
5.5%
M 2092
 
4.5%
T 1662
 
3.6%
Other values (8) 7286
15.8%
Common
ValueCountFrequency (%)
2092
72.3%
. 802
 
27.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48560
99.0%
None 488
 
1.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 6848
14.1%
N 6420
13.2%
O 5347
11.0%
I 4130
8.5%
D 3825
7.9%
E 3126
 
6.4%
R 2883
 
5.9%
G 2535
 
5.2%
2092
 
4.3%
M 2092
 
4.3%
Other values (9) 9262
19.1%
None
ValueCountFrequency (%)
É 488
100.0%
Distinct76
Distinct (%)1.9%
Missing180
Missing (%)4.2%
Infinite0
Infinite (%)0.0%
Mean54.247801
Minimum22
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-02-28T14:19:09.953461image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile33
Q145
median54
Q364
95-th percentile78
Maximum98
Range76
Interquartile range (IQR)19

Descriptive statistics

Standard deviation13.574088
Coefficient of variation (CV)0.25022375
Kurtosis-0.39661078
Mean54.247801
Median Absolute Deviation (MAD)10
Skewness0.19871813
Sum221982
Variance184.25586
MonotonicityNot monotonic
2023-02-28T14:19:10.324925image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 122
 
2.9%
55 121
 
2.8%
47 121
 
2.8%
57 119
 
2.8%
58 118
 
2.8%
48 116
 
2.7%
53 116
 
2.7%
51 111
 
2.6%
45 109
 
2.6%
56 109
 
2.6%
Other values (66) 2930
68.6%
(Missing) 180
 
4.2%
ValueCountFrequency (%)
22 3
 
0.1%
23 1
 
< 0.1%
24 9
 
0.2%
25 12
 
0.3%
26 11
 
0.3%
27 14
0.3%
28 14
0.3%
29 20
0.5%
30 32
0.7%
31 33
0.8%
ValueCountFrequency (%)
98 1
 
< 0.1%
97 2
 
< 0.1%
96 1
 
< 0.1%
95 1
 
< 0.1%
93 2
 
< 0.1%
92 2
 
< 0.1%
91 5
0.1%
90 4
0.1%
89 4
0.1%
88 5
0.1%

sexo
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)< 0.1%
Missing147
Missing (%)3.4%
Memory size33.5 KiB
Feminino
4090 
Masculino
 
35

Length

Max length9
Median length8
Mean length8.0084848
Min length8

Characters and Unicode

Total characters33035
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFeminino
2nd rowFeminino
3rd rowFeminino
4th rowFeminino
5th rowFeminino

Common Values

ValueCountFrequency (%)
Feminino 4090
95.7%
Masculino 35
 
0.8%
(Missing) 147
 
3.4%

Length

2023-02-28T14:19:10.679579image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:11.007179image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
feminino 4090
99.2%
masculino 35
 
0.8%

Most occurring characters

ValueCountFrequency (%)
i 8215
24.9%
n 8215
24.9%
o 4125
12.5%
F 4090
12.4%
e 4090
12.4%
m 4090
12.4%
M 35
 
0.1%
a 35
 
0.1%
s 35
 
0.1%
c 35
 
0.1%
Other values (2) 70
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 28910
87.5%
Uppercase Letter 4125
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 8215
28.4%
n 8215
28.4%
o 4125
14.3%
e 4090
14.1%
m 4090
14.1%
a 35
 
0.1%
s 35
 
0.1%
c 35
 
0.1%
u 35
 
0.1%
l 35
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
F 4090
99.2%
M 35
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 33035
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 8215
24.9%
n 8215
24.9%
o 4125
12.5%
F 4090
12.4%
e 4090
12.4%
m 4090
12.4%
M 35
 
0.1%
a 35
 
0.1%
s 35
 
0.1%
c 35
 
0.1%
Other values (2) 70
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33035
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 8215
24.9%
n 8215
24.9%
o 4125
12.5%
F 4090
12.4%
e 4090
12.4%
m 4090
12.4%
M 35
 
0.1%
a 35
 
0.1%
s 35
 
0.1%
c 35
 
0.1%
Other values (2) 70
 
0.2%
Distinct5
Distinct (%)2.1%
Missing4038
Missing (%)94.5%
Memory size33.5 KiB
Branco
100 
Pardo
71 
Negro
45 
Outro
13 
Asiático
 
5

Length

Max length8
Median length5
Mean length5.491453
Min length5

Characters and Unicode

Total characters1285
Distinct characters18
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBranco
2nd rowBranco
3rd rowBranco
4th rowBranco
5th rowPardo

Common Values

ValueCountFrequency (%)
Branco 100
 
2.3%
Pardo 71
 
1.7%
Negro 45
 
1.1%
Outro 13
 
0.3%
Asiático 5
 
0.1%
(Missing) 4038
94.5%

Length

2023-02-28T14:19:11.278633image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:11.620003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
branco 100
42.7%
pardo 71
30.3%
negro 45
19.2%
outro 13
 
5.6%
asiático 5
 
2.1%

Most occurring characters

ValueCountFrequency (%)
o 234
18.2%
r 229
17.8%
a 171
13.3%
c 105
8.2%
B 100
7.8%
n 100
7.8%
P 71
 
5.5%
d 71
 
5.5%
g 45
 
3.5%
e 45
 
3.5%
Other values (8) 114
8.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1051
81.8%
Uppercase Letter 234
 
18.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 234
22.3%
r 229
21.8%
a 171
16.3%
c 105
10.0%
n 100
9.5%
d 71
 
6.8%
g 45
 
4.3%
e 45
 
4.3%
t 18
 
1.7%
u 13
 
1.2%
Other values (3) 20
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
B 100
42.7%
P 71
30.3%
N 45
19.2%
O 13
 
5.6%
A 5
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 1285
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 234
18.2%
r 229
17.8%
a 171
13.3%
c 105
8.2%
B 100
7.8%
n 100
7.8%
P 71
 
5.5%
d 71
 
5.5%
g 45
 
3.5%
e 45
 
3.5%
Other values (8) 114
8.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1280
99.6%
None 5
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 234
18.3%
r 229
17.9%
a 171
13.4%
c 105
8.2%
B 100
7.8%
n 100
7.8%
P 71
 
5.5%
d 71
 
5.5%
g 45
 
3.5%
e 45
 
3.5%
Other values (7) 109
8.5%
None
ValueCountFrequency (%)
á 5
100.0%

uf_de_nascimento_do_paciente
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing4270
Missing (%)> 99.9%
Memory size33.5 KiB
SP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSP
2nd rowSP

Common Values

ValueCountFrequency (%)
SP 2
 
< 0.1%
(Missing) 4270
> 99.9%

Length

2023-02-28T14:19:11.814713image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:12.073874image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
sp 2
100.0%

Most occurring characters

ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

uf_de_residencia_do_paciente
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)50.0%
Missing4270
Missing (%)> 99.9%
Memory size33.5 KiB
SP

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSP
2nd rowSP

Common Values

ValueCountFrequency (%)
SP 2
 
< 0.1%
(Missing) 4270
> 99.9%

Length

2023-02-28T14:19:12.314280image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:12.647939image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
sp 2
100.0%

Most occurring characters

ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 2
50.0%
P 2
50.0%

data_da_ultima_informacao_sobre_o_paciente
Categorical

HIGH CARDINALITY  UNIFORM 

Distinct2131
Distinct (%)49.9%
Missing2
Missing (%)< 0.1%
Memory size33.5 KiB
2020-07-08
 
9
2020-05-26
 
7
2020-01-25
 
7
2019-12-26
 
7
2020-04-30
 
7
Other values (2126)
4233 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters42700
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1033 ?
Unique (%)24.2%

Sample

1st row2014-04-26
2nd row2016-11-17
3rd row2019-05-02
4th row2011-09-29
5th row2017-05-24

Common Values

ValueCountFrequency (%)
2020-07-08 9
 
0.2%
2020-05-26 7
 
0.2%
2020-01-25 7
 
0.2%
2019-12-26 7
 
0.2%
2020-04-30 7
 
0.2%
2020-09-17 7
 
0.2%
2019-08-06 7
 
0.2%
2020-09-18 7
 
0.2%
2019-09-18 7
 
0.2%
2019-08-18 7
 
0.2%
Other values (2121) 4198
98.3%

Length

2023-02-28T14:19:12.868003image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2020-07-08 9
 
0.2%
2019-08-06 7
 
0.2%
2020-05-26 7
 
0.2%
2019-09-18 7
 
0.2%
2020-09-18 7
 
0.2%
2019-08-18 7
 
0.2%
2020-09-17 7
 
0.2%
2020-04-30 7
 
0.2%
2019-12-26 7
 
0.2%
2020-01-25 7
 
0.2%
Other values (2121) 4198
98.3%

Most occurring characters

ValueCountFrequency (%)
0 10538
24.7%
- 8540
20.0%
2 8343
19.5%
1 6938
16.2%
9 1765
 
4.1%
8 1294
 
3.0%
7 1289
 
3.0%
3 1143
 
2.7%
6 1012
 
2.4%
5 975
 
2.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34160
80.0%
Dash Punctuation 8540
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10538
30.8%
2 8343
24.4%
1 6938
20.3%
9 1765
 
5.2%
8 1294
 
3.8%
7 1289
 
3.8%
3 1143
 
3.3%
6 1012
 
3.0%
5 975
 
2.9%
4 863
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 8540
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42700
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10538
24.7%
- 8540
20.0%
2 8343
19.5%
1 6938
16.2%
9 1765
 
4.1%
8 1294
 
3.0%
7 1289
 
3.0%
3 1143
 
2.7%
6 1012
 
2.4%
5 975
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42700
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10538
24.7%
- 8540
20.0%
2 8343
19.5%
1 6938
16.2%
9 1765
 
4.1%
8 1294
 
3.0%
7 1289
 
3.0%
3 1143
 
2.7%
6 1012
 
2.4%
5 975
 
2.3%
Distinct4
Distinct (%)0.1%
Missing2
Missing (%)< 0.1%
Memory size33.5 KiB
Vivo, SOE
2815 
Obito por câncer
1131 
Vivo, com câncer
 
235
Óbito por outras causas, SOE
 
89

Length

Max length28
Median length9
Mean length11.635363
Min length9

Characters and Unicode

Total characters49683
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowObito por câncer
2nd rowVivo, SOE
3rd rowVivo, SOE
4th rowObito por câncer
5th rowVivo, SOE

Common Values

ValueCountFrequency (%)
Vivo, SOE 2815
65.9%
Obito por câncer 1131
26.5%
Vivo, com câncer 235
 
5.5%
Óbito por outras causas, SOE 89
 
2.1%
(Missing) 2
 
< 0.1%

Length

2023-02-28T14:19:13.144007image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:13.524538image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
vivo 3050
30.0%
soe 2904
28.5%
câncer 1366
13.4%
por 1220
 
12.0%
obito 1131
 
11.1%
com 235
 
2.3%
óbito 89
 
0.9%
outras 89
 
0.9%
causas 89
 
0.9%

Most occurring characters

ValueCountFrequency (%)
5903
11.9%
o 5814
11.7%
i 4270
 
8.6%
O 4035
 
8.1%
, 3139
 
6.3%
c 3056
 
6.2%
V 3050
 
6.1%
v 3050
 
6.1%
S 2904
 
5.8%
E 2904
 
5.8%
Other values (12) 11558
23.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 27659
55.7%
Uppercase Letter 12982
26.1%
Space Separator 5903
 
11.9%
Other Punctuation 3139
 
6.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 5814
21.0%
i 4270
15.4%
c 3056
11.0%
v 3050
11.0%
r 2675
9.7%
n 1366
 
4.9%
e 1366
 
4.9%
â 1366
 
4.9%
t 1309
 
4.7%
p 1220
 
4.4%
Other values (5) 2167
 
7.8%
Uppercase Letter
ValueCountFrequency (%)
O 4035
31.1%
V 3050
23.5%
S 2904
22.4%
E 2904
22.4%
Ó 89
 
0.7%
Space Separator
ValueCountFrequency (%)
5903
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3139
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 40641
81.8%
Common 9042
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 5814
14.3%
i 4270
10.5%
O 4035
9.9%
c 3056
7.5%
V 3050
7.5%
v 3050
7.5%
S 2904
 
7.1%
E 2904
 
7.1%
r 2675
 
6.6%
n 1366
 
3.4%
Other values (10) 7517
18.5%
Common
ValueCountFrequency (%)
5903
65.3%
, 3139
34.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 48228
97.1%
None 1455
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5903
12.2%
o 5814
12.1%
i 4270
8.9%
O 4035
 
8.4%
, 3139
 
6.5%
c 3056
 
6.3%
V 3050
 
6.3%
v 3050
 
6.3%
S 2904
 
6.0%
E 2904
 
6.0%
Other values (10) 10103
20.9%
None
ValueCountFrequency (%)
â 1366
93.9%
Ó 89
 
6.1%
Distinct2071
Distinct (%)48.5%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean1475.0037
Minimum0
Maximum4503
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-02-28T14:19:13.826529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile359
Q1956.25
median1282
Q31817.75
95-th percentile3272.55
Maximum4503
Range4503
Interquartile range (IQR)861.5

Descriptive statistics

Standard deviation859.62238
Coefficient of variation (CV)0.58279335
Kurtosis0.33156452
Mean1475.0037
Median Absolute Deviation (MAD)397
Skewness0.9481852
Sum6298266
Variance738950.63
MonotonicityNot monotonic
2023-02-28T14:19:14.167856image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1417 14
 
0.3%
1407 14
 
0.3%
1408 13
 
0.3%
1435 12
 
0.3%
1162 12
 
0.3%
1379 11
 
0.3%
1189 11
 
0.3%
1412 11
 
0.3%
1406 11
 
0.3%
1404 10
 
0.2%
Other values (2061) 4151
97.2%
ValueCountFrequency (%)
0 1
< 0.1%
6 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
13 1
< 0.1%
16 1
< 0.1%
25 1
< 0.1%
30 1
< 0.1%
31 1
< 0.1%
ValueCountFrequency (%)
4503 1
< 0.1%
4474 1
< 0.1%
4395 1
< 0.1%
4381 1
< 0.1%
4330 1
< 0.1%
4326 1
< 0.1%
4295 1
< 0.1%
4277 1
< 0.1%
4235 1
< 0.1%
4231 1
< 0.1%

ja_ficou_gravida
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing3259
Missing (%)76.3%
Memory size33.5 KiB
Sim
1002 
Não
 
11

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3039
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Sim 1002
 
23.5%
Não 11
 
0.3%
(Missing) 3259
76.3%

Length

2023-02-28T14:19:14.858682image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:15.027942image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
sim 1002
98.9%
não 11
 
1.1%

Most occurring characters

ValueCountFrequency (%)
S 1002
33.0%
i 1002
33.0%
m 1002
33.0%
N 11
 
0.4%
ã 11
 
0.4%
o 11
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2026
66.7%
Uppercase Letter 1013
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1002
49.5%
m 1002
49.5%
ã 11
 
0.5%
o 11
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
S 1002
98.9%
N 11
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 3039
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 1002
33.0%
i 1002
33.0%
m 1002
33.0%
N 11
 
0.4%
ã 11
 
0.4%
o 11
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3028
99.6%
None 11
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 1002
33.1%
i 1002
33.1%
m 1002
33.1%
N 11
 
0.4%
o 11
 
0.4%
None
ValueCountFrequency (%)
ã 11
100.0%
Distinct6
Distinct (%)13.6%
Missing4228
Missing (%)99.0%
Infinite0
Infinite (%)0.0%
Mean2.3181818
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-02-28T14:19:15.160185image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile5
Maximum7
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4104713
Coefficient of variation (CV)0.60843858
Kurtosis1.5772173
Mean2.3181818
Median Absolute Deviation (MAD)1
Skewness1.2235794
Sum102
Variance1.9894292
MonotonicityNot monotonic
2023-02-28T14:19:15.320700image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
1 16
 
0.4%
2 11
 
0.3%
3 10
 
0.2%
4 3
 
0.1%
5 3
 
0.1%
7 1
 
< 0.1%
(Missing) 4228
99.0%
ValueCountFrequency (%)
1 16
0.4%
2 11
0.3%
3 10
0.2%
4 3
 
0.1%
5 3
 
0.1%
7 1
 
< 0.1%
ValueCountFrequency (%)
7 1
 
< 0.1%
5 3
 
0.1%
4 3
 
0.1%
3 10
0.2%
2 11
0.3%
1 16
0.4%

numero_de_partos
Categorical

MISSING  UNIFORM 

Distinct2
Distinct (%)100.0%
Missing4270
Missing (%)> 99.9%
Memory size33.5 KiB
2.0
1.0

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2.0
2nd row1.0

Common Values

ValueCountFrequency (%)
2.0 1
 
< 0.1%
1.0 1
 
< 0.1%
(Missing) 4270
> 99.9%

Length

2023-02-28T14:19:15.492171image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:15.672029image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2.0 1
50.0%
1.0 1
50.0%

Most occurring characters

ValueCountFrequency (%)
. 2
33.3%
0 2
33.3%
2 1
16.7%
1 1
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
66.7%
Other Punctuation 2
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2
50.0%
2 1
25.0%
1 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 2
33.3%
0 2
33.3%
2 1
16.7%
1 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 2
33.3%
0 2
33.3%
2 1
16.7%
1 1
16.7%
Distinct36
Distinct (%)4.0%
Missing3375
Missing (%)79.0%
Infinite0
Infinite (%)0.0%
Mean23.057971
Minimum0
Maximum53
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-02-28T14:19:15.818731image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile16
Q119
median22
Q326
95-th percentile33
Maximum53
Range53
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.6652317
Coefficient of variation (CV)0.24569515
Kurtosis1.7550002
Mean23.057971
Median Absolute Deviation (MAD)3
Skewness0.79315429
Sum20683
Variance32.09485
MonotonicityNot monotonic
2023-02-28T14:19:16.027196image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
19 90
 
2.1%
21 75
 
1.8%
20 75
 
1.8%
23 69
 
1.6%
22 61
 
1.4%
18 61
 
1.4%
24 53
 
1.2%
17 51
 
1.2%
26 44
 
1.0%
25 39
 
0.9%
Other values (26) 279
 
6.5%
(Missing) 3375
79.0%
ValueCountFrequency (%)
0 2
 
< 0.1%
11 1
 
< 0.1%
12 2
 
< 0.1%
13 5
 
0.1%
14 8
 
0.2%
15 17
 
0.4%
16 28
 
0.7%
17 51
1.2%
18 61
1.4%
19 90
2.1%
ValueCountFrequency (%)
53 1
 
< 0.1%
45 2
 
< 0.1%
44 1
 
< 0.1%
42 2
 
< 0.1%
41 1
 
< 0.1%
40 1
 
< 0.1%
39 2
 
< 0.1%
38 3
0.1%
37 7
0.2%
36 5
0.1%

abortou
Categorical

Distinct2
Distinct (%)3.8%
Missing4220
Missing (%)98.8%
Memory size33.5 KiB
Não
41 
Sim
11 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters156
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Não 41
 
1.0%
Sim 11
 
0.3%
(Missing) 4220
98.8%

Length

2023-02-28T14:19:16.216843image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:16.392373image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
não 41
78.8%
sim 11
 
21.2%

Most occurring characters

ValueCountFrequency (%)
N 41
26.3%
ã 41
26.3%
o 41
26.3%
S 11
 
7.1%
i 11
 
7.1%
m 11
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 104
66.7%
Uppercase Letter 52
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã 41
39.4%
o 41
39.4%
i 11
 
10.6%
m 11
 
10.6%
Uppercase Letter
ValueCountFrequency (%)
N 41
78.8%
S 11
 
21.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 156
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 41
26.3%
ã 41
26.3%
o 41
26.3%
S 11
 
7.1%
i 11
 
7.1%
m 11
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 115
73.7%
None 41
 
26.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 41
35.7%
o 41
35.7%
S 11
 
9.6%
i 11
 
9.6%
m 11
 
9.6%
None
ValueCountFrequency (%)
ã 41
100.0%
Distinct2
Distinct (%)0.2%
Missing3230
Missing (%)75.6%
Memory size33.5 KiB
Sim
789 
Não
253 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters3126
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowNão
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim 789
 
18.5%
Não 253
 
5.9%
(Missing) 3230
75.6%

Length

2023-02-28T14:19:16.544693image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:16.725281image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
sim 789
75.7%
não 253
 
24.3%

Most occurring characters

ValueCountFrequency (%)
S 789
25.2%
i 789
25.2%
m 789
25.2%
N 253
 
8.1%
ã 253
 
8.1%
o 253
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2084
66.7%
Uppercase Letter 1042
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 789
37.9%
m 789
37.9%
ã 253
 
12.1%
o 253
 
12.1%
Uppercase Letter
ValueCountFrequency (%)
S 789
75.7%
N 253
 
24.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3126
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 789
25.2%
i 789
25.2%
m 789
25.2%
N 253
 
8.1%
ã 253
 
8.1%
o 253
 
8.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2873
91.9%
None 253
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 789
27.5%
i 789
27.5%
m 789
27.5%
N 253
 
8.8%
o 253
 
8.8%
None
ValueCountFrequency (%)
ã 253
100.0%
Distinct56
Distinct (%)8.1%
Missing3584
Missing (%)83.9%
Infinite0
Infinite (%)0.0%
Mean19.043605
Minimum0
Maximum260
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-02-28T14:19:16.888679image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q16
median12
Q324
95-th percentile60
Maximum260
Range260
Interquartile range (IQR)18

Descriptive statistics

Standard deviation23.10506
Coefficient of variation (CV)1.2132714
Kurtosis33.704156
Mean19.043605
Median Absolute Deviation (MAD)8
Skewness4.4078431
Sum13102
Variance533.8438
MonotonicityNot monotonic
2023-02-28T14:19:17.123949image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 88
 
2.1%
6 79
 
1.8%
24 75
 
1.8%
36 49
 
1.1%
3 46
 
1.1%
4 38
 
0.9%
2 37
 
0.9%
8 25
 
0.6%
1 24
 
0.6%
18 23
 
0.5%
Other values (46) 204
 
4.8%
(Missing) 3584
83.9%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 24
 
0.6%
2 37
0.9%
3 46
1.1%
4 38
0.9%
5 14
 
0.3%
6 79
1.8%
7 13
 
0.3%
8 25
 
0.6%
9 11
 
0.3%
ValueCountFrequency (%)
260 1
 
< 0.1%
240 1
 
< 0.1%
178 1
 
< 0.1%
150 1
 
< 0.1%
120 1
 
< 0.1%
100 1
 
< 0.1%
96 1
 
< 0.1%
84 3
0.1%
82 1
 
< 0.1%
80 1
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4269 
Checked
 
3

Length

Max length9
Median length9
Mean length8.9985955
Min length7

Characters and Unicode

Total characters38442
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4269
99.9%
Checked 3
 
0.1%

Length

2023-02-28T14:19:17.351550image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:17.549672image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4269
99.9%
checked 3
 
0.1%

Most occurring characters

ValueCountFrequency (%)
e 8544
22.2%
c 8541
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4269
11.1%
n 4269
11.1%
C 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34170
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8544
25.0%
c 8541
25.0%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
n 4269
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4269
99.9%
C 3
 
0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 38442
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8544
22.2%
c 8541
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4269
11.1%
n 4269
11.1%
C 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38442
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8544
22.2%
c 8541
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4269
11.1%
n 4269
11.1%
C 3
 
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4232 
Checked
 
40

Length

Max length9
Median length9
Mean length8.9812734
Min length7

Characters and Unicode

Total characters38368
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4232
99.1%
Checked 40
 
0.9%

Length

2023-02-28T14:19:17.714844image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:17.904909image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4232
99.1%
checked 40
 
0.9%

Most occurring characters

ValueCountFrequency (%)
e 8544
22.3%
c 8504
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4232
11.0%
n 4232
11.0%
C 40
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34096
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8544
25.1%
c 8504
24.9%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
n 4232
12.4%
Uppercase Letter
ValueCountFrequency (%)
U 4232
99.1%
C 40
 
0.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 38368
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8544
22.3%
c 8504
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4232
11.0%
n 4232
11.0%
C 40
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38368
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8544
22.3%
c 8504
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4232
11.0%
n 4232
11.0%
C 40
 
0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4264 
Checked
 
8

Length

Max length9
Median length9
Mean length8.9962547
Min length7

Characters and Unicode

Total characters38432
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4264
99.8%
Checked 8
 
0.2%

Length

2023-02-28T14:19:18.057647image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:18.248856image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4264
99.8%
checked 8
 
0.2%

Most occurring characters

ValueCountFrequency (%)
e 8544
22.2%
c 8536
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4264
11.1%
n 4264
11.1%
C 8
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34160
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8544
25.0%
c 8536
25.0%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
n 4264
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4264
99.8%
C 8
 
0.2%

Most occurring scripts

ValueCountFrequency (%)
Latin 38432
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8544
22.2%
c 8536
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4264
11.1%
n 4264
11.1%
C 8
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8544
22.2%
c 8536
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4264
11.1%
n 4264
11.1%
C 8
 
< 0.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4272 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters38448
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4272
100.0%

Length

2023-02-28T14:19:18.392361image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:18.573133image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4272
100.0%

Most occurring characters

ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34176
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 8544
25.0%
e 8544
25.0%
n 4272
12.5%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4272 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters38448
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4272
100.0%

Length

2023-02-28T14:19:18.709144image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:18.883033image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4272
100.0%

Most occurring characters

ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34176
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 8544
25.0%
e 8544
25.0%
n 4272
12.5%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
Distinct17
Distinct (%)1.7%
Missing3247
Missing (%)76.0%
Infinite0
Infinite (%)0.0%
Mean12.891707
Minimum0
Maximum37
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size33.5 KiB
2023-02-28T14:19:19.014380image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q112
median13
Q314
95-th percentile16
Maximum37
Range37
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1044455
Coefficient of variation (CV)0.16324025
Kurtosis21.516307
Mean12.891707
Median Absolute Deviation (MAD)1
Skewness1.9044226
Sum13214
Variance4.4286909
MonotonicityNot monotonic
2023-02-28T14:19:19.189870image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
12 225
 
5.3%
13 213
 
5.0%
14 162
 
3.8%
11 154
 
3.6%
15 115
 
2.7%
16 43
 
1.0%
10 40
 
0.9%
9 33
 
0.8%
17 23
 
0.5%
18 7
 
0.2%
Other values (7) 10
 
0.2%
(Missing) 3247
76.0%
ValueCountFrequency (%)
0 1
 
< 0.1%
7 1
 
< 0.1%
8 3
 
0.1%
9 33
 
0.8%
10 40
 
0.9%
11 154
3.6%
12 225
5.3%
13 213
5.0%
14 162
3.8%
15 115
2.7%
ValueCountFrequency (%)
37 1
 
< 0.1%
30 1
 
< 0.1%
20 1
 
< 0.1%
19 2
 
< 0.1%
18 7
 
0.2%
17 23
 
0.5%
16 43
 
1.0%
15 115
2.7%
14 162
3.8%
13 213
5.0%
Distinct2
Distinct (%)66.7%
Missing4269
Missing (%)99.9%
Memory size33.5 KiB
Não
Sim

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowNão
2nd rowSim
3rd rowNão

Common Values

ValueCountFrequency (%)
Não 2
 
< 0.1%
Sim 1
 
< 0.1%
(Missing) 4269
99.9%

Length

2023-02-28T14:19:19.376364image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:19.577757image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
não 2
66.7%
sim 1
33.3%

Most occurring characters

ValueCountFrequency (%)
N 2
22.2%
ã 2
22.2%
o 2
22.2%
S 1
11.1%
i 1
11.1%
m 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6
66.7%
Uppercase Letter 3
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã 2
33.3%
o 2
33.3%
i 1
16.7%
m 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 2
66.7%
S 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 9
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2
22.2%
ã 2
22.2%
o 2
22.2%
S 1
11.1%
i 1
11.1%
m 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
77.8%
None 2
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 2
28.6%
o 2
28.6%
S 1
14.3%
i 1
14.3%
m 1
14.3%
None
ValueCountFrequency (%)
ã 2
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4271 
Checked
 
1

Length

Max length9
Median length9
Mean length8.9995318
Min length7

Characters and Unicode

Total characters38446
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4271
> 99.9%
Checked 1
 
< 0.1%

Length

2023-02-28T14:19:19.741697image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:20.180182image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4271
> 99.9%
checked 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 8544
22.2%
c 8543
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4271
11.1%
n 4271
11.1%
C 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34174
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8544
25.0%
c 8543
25.0%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
n 4271
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4271
> 99.9%
C 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 38446
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8544
22.2%
c 8543
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4271
11.1%
n 4271
11.1%
C 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38446
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8544
22.2%
c 8543
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4271
11.1%
n 4271
11.1%
C 1
 
< 0.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4272 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters38448
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4272
100.0%

Length

2023-02-28T14:19:20.510541image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:20.840002image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4272
100.0%

Most occurring characters

ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34176
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 8544
25.0%
e 8544
25.0%
n 4272
12.5%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4272 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters38448
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4272
100.0%

Length

2023-02-28T14:19:21.155194image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:21.545076image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4272
100.0%

Most occurring characters

ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34176
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 8544
25.0%
e 8544
25.0%
n 4272
12.5%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4272 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters38448
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4272
100.0%

Length

2023-02-28T14:19:21.834070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:22.164869image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4272
100.0%

Most occurring characters

ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34176
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 8544
25.0%
e 8544
25.0%
n 4272
12.5%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4272 

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters38448
Distinct characters7
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4272
100.0%

Length

2023-02-28T14:19:22.448429image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:22.818392image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4272
100.0%

Most occurring characters

ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34176
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
c 8544
25.0%
e 8544
25.0%
n 4272
12.5%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
Uppercase Letter
ValueCountFrequency (%)
U 4272
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 38448
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38448
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
c 8544
22.2%
e 8544
22.2%
U 4272
11.1%
n 4272
11.1%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%

ja_fez_uso_de_drogas
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)1.3%
Missing4123
Missing (%)96.5%
Memory size33.5 KiB
Não
148 
Sim
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters447
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st rowNão
2nd rowNão
3rd rowNão
4th rowNão
5th rowNão

Common Values

ValueCountFrequency (%)
Não 148
 
3.5%
Sim 1
 
< 0.1%
(Missing) 4123
96.5%

Length

2023-02-28T14:19:23.277190image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:23.717689image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
não 148
99.3%
sim 1
 
0.7%

Most occurring characters

ValueCountFrequency (%)
N 148
33.1%
ã 148
33.1%
o 148
33.1%
S 1
 
0.2%
i 1
 
0.2%
m 1
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 298
66.7%
Uppercase Letter 149
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
ã 148
49.7%
o 148
49.7%
i 1
 
0.3%
m 1
 
0.3%
Uppercase Letter
ValueCountFrequency (%)
N 148
99.3%
S 1
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 447
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 148
33.1%
ã 148
33.1%
o 148
33.1%
S 1
 
0.2%
i 1
 
0.2%
m 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 299
66.9%
None 148
33.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 148
49.5%
o 148
49.5%
S 1
 
0.3%
i 1
 
0.3%
m 1
 
0.3%
None
ValueCountFrequency (%)
ã 148
100.0%

atividade_fisica
Categorical

Distinct4
Distinct (%)1.3%
Missing3967
Missing (%)92.9%
Memory size33.5 KiB
Não pratica
223 
Pratica regularmente
43 
Pratica esporadicamente
23 
Pratica frequentemente
 
16

Length

Max length23
Median length11
Mean length13.75082
Min length11

Characters and Unicode

Total characters4194
Distinct characters21
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPratica regularmente
2nd rowNão pratica
3rd rowNão pratica
4th rowNão pratica
5th rowPratica regularmente

Common Values

ValueCountFrequency (%)
Não pratica 223
 
5.2%
Pratica regularmente 43
 
1.0%
Pratica esporadicamente 23
 
0.5%
Pratica frequentemente 16
 
0.4%
(Missing) 3967
92.9%

Length

2023-02-28T14:19:24.063774image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:24.429529image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
pratica 305
50.0%
não 223
36.6%
regularmente 43
 
7.0%
esporadicamente 23
 
3.8%
frequentemente 16
 
2.6%

Most occurring characters

ValueCountFrequency (%)
a 699
16.7%
r 430
10.3%
t 403
9.6%
i 328
7.8%
c 328
7.8%
305
7.3%
e 278
 
6.6%
o 246
 
5.9%
p 246
 
5.9%
N 223
 
5.3%
Other values (11) 708
16.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3584
85.5%
Space Separator 305
 
7.3%
Uppercase Letter 305
 
7.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 699
19.5%
r 430
12.0%
t 403
11.2%
i 328
9.2%
c 328
9.2%
e 278
 
7.8%
o 246
 
6.9%
p 246
 
6.9%
ã 223
 
6.2%
n 98
 
2.7%
Other values (8) 305
8.5%
Uppercase Letter
ValueCountFrequency (%)
N 223
73.1%
P 82
 
26.9%
Space Separator
ValueCountFrequency (%)
305
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3889
92.7%
Common 305
 
7.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 699
18.0%
r 430
11.1%
t 403
10.4%
i 328
8.4%
c 328
8.4%
e 278
 
7.1%
o 246
 
6.3%
p 246
 
6.3%
N 223
 
5.7%
ã 223
 
5.7%
Other values (10) 485
12.5%
Common
ValueCountFrequency (%)
305
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3971
94.7%
None 223
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 699
17.6%
r 430
10.8%
t 403
10.1%
i 328
8.3%
c 328
8.3%
305
7.7%
e 278
 
7.0%
o 246
 
6.2%
p 246
 
6.2%
N 223
 
5.6%
Other values (10) 485
12.2%
None
ValueCountFrequency (%)
ã 223
100.0%
Distinct4
Distinct (%)1.9%
Missing4060
Missing (%)95.0%
Memory size33.5 KiB
Nunca fumou
148 
Fumou no passado
34 
Fuma atualmente
27 
não-informado
 
3

Length

Max length16
Median length11
Mean length12.339623
Min length11

Characters and Unicode

Total characters2616
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNunca fumou
2nd rowFumou no passado
3rd rowNunca fumou
4th rowFuma atualmente
5th rowNunca fumou

Common Values

ValueCountFrequency (%)
Nunca fumou 148
 
3.5%
Fumou no passado 34
 
0.8%
Fuma atualmente 27
 
0.6%
não-informado 3
 
0.1%
(Missing) 4060
95.0%

Length

2023-02-28T14:19:25.108855image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:25.645586image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
fumou 182
40.0%
nunca 148
32.5%
no 34
 
7.5%
passado 34
 
7.5%
fuma 27
 
5.9%
atualmente 27
 
5.9%
não-informado 3
 
0.7%

Most occurring characters

ValueCountFrequency (%)
u 566
21.6%
a 300
11.5%
o 259
9.9%
243
9.3%
m 239
9.1%
n 215
 
8.2%
f 151
 
5.8%
N 148
 
5.7%
c 148
 
5.7%
s 68
 
2.6%
Other values (10) 279
10.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2161
82.6%
Space Separator 243
 
9.3%
Uppercase Letter 209
 
8.0%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 566
26.2%
a 300
13.9%
o 259
12.0%
m 239
11.1%
n 215
 
9.9%
f 151
 
7.0%
c 148
 
6.8%
s 68
 
3.1%
e 54
 
2.5%
t 54
 
2.5%
Other values (6) 107
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
N 148
70.8%
F 61
29.2%
Space Separator
ValueCountFrequency (%)
243
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2370
90.6%
Common 246
 
9.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 566
23.9%
a 300
12.7%
o 259
10.9%
m 239
10.1%
n 215
 
9.1%
f 151
 
6.4%
N 148
 
6.2%
c 148
 
6.2%
s 68
 
2.9%
F 61
 
2.6%
Other values (8) 215
 
9.1%
Common
ValueCountFrequency (%)
243
98.8%
- 3
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2613
99.9%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 566
21.7%
a 300
11.5%
o 259
9.9%
243
9.3%
m 239
9.1%
n 215
 
8.2%
f 151
 
5.8%
N 148
 
5.7%
c 148
 
5.7%
s 68
 
2.6%
Other values (9) 276
10.6%
None
ValueCountFrequency (%)
ã 3
100.0%

consumo_de_alcool
Categorical

IMBALANCE  MISSING 

Distinct4
Distinct (%)2.0%
Missing4068
Missing (%)95.2%
Memory size33.5 KiB
Nunca bebeu
159 
Bebia no passado
35 
Bebe atualmente
 
6
não-informado
 
4

Length

Max length16
Median length11
Mean length12.014706
Min length11

Characters and Unicode

Total characters2451
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBebe atualmente
2nd rowBebia no passado
3rd rowBebia no passado
4th rowNunca bebeu
5th rowBebia no passado

Common Values

ValueCountFrequency (%)
Nunca bebeu 159
 
3.7%
Bebia no passado 35
 
0.8%
Bebe atualmente 6
 
0.1%
não-informado 4
 
0.1%
(Missing) 4068
95.2%

Length

2023-02-28T14:19:25.924503image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:26.266535image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
nunca 159
36.2%
bebeu 159
36.2%
bebia 35
 
8.0%
no 35
 
8.0%
passado 35
 
8.0%
bebe 6
 
1.4%
atualmente 6
 
1.4%
não-informado 4
 
0.9%

Most occurring characters

ValueCountFrequency (%)
e 377
15.4%
b 359
14.6%
u 324
13.2%
a 280
11.4%
235
9.6%
n 208
8.5%
N 159
6.5%
c 159
6.5%
o 82
 
3.3%
s 70
 
2.9%
Other values (11) 198
8.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2012
82.1%
Space Separator 235
 
9.6%
Uppercase Letter 200
 
8.2%
Dash Punctuation 4
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 377
18.7%
b 359
17.8%
u 324
16.1%
a 280
13.9%
n 208
10.3%
c 159
7.9%
o 82
 
4.1%
s 70
 
3.5%
i 39
 
1.9%
d 39
 
1.9%
Other values (7) 75
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
N 159
79.5%
B 41
 
20.5%
Space Separator
ValueCountFrequency (%)
235
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2212
90.2%
Common 239
 
9.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 377
17.0%
b 359
16.2%
u 324
14.6%
a 280
12.7%
n 208
9.4%
N 159
7.2%
c 159
7.2%
o 82
 
3.7%
s 70
 
3.2%
B 41
 
1.9%
Other values (9) 153
6.9%
Common
ValueCountFrequency (%)
235
98.3%
- 4
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2447
99.8%
None 4
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 377
15.4%
b 359
14.7%
u 324
13.2%
a 280
11.4%
235
9.6%
n 208
8.5%
N 159
6.5%
c 159
6.5%
o 82
 
3.4%
s 70
 
2.9%
Other values (10) 194
7.9%
None
ValueCountFrequency (%)
ã 4
100.0%
Distinct2
Distinct (%)1.1%
Missing4082
Missing (%)95.6%
Memory size33.5 KiB
Sim
138 
Não
52 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters570
Distinct characters6
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowNão
3rd rowNão
4th rowSim
5th rowNão

Common Values

ValueCountFrequency (%)
Sim 138
 
3.2%
Não 52
 
1.2%
(Missing) 4082
95.6%

Length

2023-02-28T14:19:26.455595image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:26.768569image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
sim 138
72.6%
não 52
 
27.4%

Most occurring characters

ValueCountFrequency (%)
S 138
24.2%
i 138
24.2%
m 138
24.2%
N 52
 
9.1%
ã 52
 
9.1%
o 52
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 380
66.7%
Uppercase Letter 190
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 138
36.3%
m 138
36.3%
ã 52
 
13.7%
o 52
 
13.7%
Uppercase Letter
ValueCountFrequency (%)
S 138
72.6%
N 52
 
27.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 570
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 138
24.2%
i 138
24.2%
m 138
24.2%
N 52
 
9.1%
ã 52
 
9.1%
o 52
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 518
90.9%
None 52
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 138
26.6%
i 138
26.6%
m 138
26.6%
N 52
 
10.0%
o 52
 
10.0%
None
ValueCountFrequency (%)
ã 52
100.0%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4183 
Checked
 
89

Length

Max length9
Median length9
Mean length8.9583333
Min length7

Characters and Unicode

Total characters38270
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4183
97.9%
Checked 89
 
2.1%

Length

2023-02-28T14:19:26.996356image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:27.336011image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4183
97.9%
checked 89
 
2.1%

Most occurring characters

ValueCountFrequency (%)
e 8544
22.3%
c 8455
22.1%
h 4272
11.2%
k 4272
11.2%
d 4272
11.2%
U 4183
10.9%
n 4183
10.9%
C 89
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 33998
88.8%
Uppercase Letter 4272
 
11.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8544
25.1%
c 8455
24.9%
h 4272
12.6%
k 4272
12.6%
d 4272
12.6%
n 4183
12.3%
Uppercase Letter
ValueCountFrequency (%)
U 4183
97.9%
C 89
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 38270
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8544
22.3%
c 8455
22.1%
h 4272
11.2%
k 4272
11.2%
d 4272
11.2%
U 4183
10.9%
n 4183
10.9%
C 89
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8544
22.3%
c 8455
22.1%
h 4272
11.2%
k 4272
11.2%
d 4272
11.2%
U 4183
10.9%
n 4183
10.9%
C 89
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4202 
Checked
 
70

Length

Max length9
Median length9
Mean length8.9672285
Min length7

Characters and Unicode

Total characters38308
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4202
98.4%
Checked 70
 
1.6%

Length

2023-02-28T14:19:27.517414image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:27.875563image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4202
98.4%
checked 70
 
1.6%

Most occurring characters

ValueCountFrequency (%)
e 8544
22.3%
c 8474
22.1%
h 4272
11.2%
k 4272
11.2%
d 4272
11.2%
U 4202
11.0%
n 4202
11.0%
C 70
 
0.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34036
88.8%
Uppercase Letter 4272
 
11.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8544
25.1%
c 8474
24.9%
h 4272
12.6%
k 4272
12.6%
d 4272
12.6%
n 4202
12.3%
Uppercase Letter
ValueCountFrequency (%)
U 4202
98.4%
C 70
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 38308
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8544
22.3%
c 8474
22.1%
h 4272
11.2%
k 4272
11.2%
d 4272
11.2%
U 4202
11.0%
n 4202
11.0%
C 70
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8544
22.3%
c 8474
22.1%
h 4272
11.2%
k 4272
11.2%
d 4272
11.2%
U 4202
11.0%
n 4202
11.0%
C 70
 
0.2%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.5 KiB
Unchecked
4224 
Checked
 
48

Length

Max length9
Median length9
Mean length8.9775281
Min length7

Characters and Unicode

Total characters38352
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUnchecked
2nd rowUnchecked
3rd rowUnchecked
4th rowUnchecked
5th rowUnchecked

Common Values

ValueCountFrequency (%)
Unchecked 4224
98.9%
Checked 48
 
1.1%

Length

2023-02-28T14:19:28.448511image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:29.315165image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
unchecked 4224
98.9%
checked 48
 
1.1%

Most occurring characters

ValueCountFrequency (%)
e 8544
22.3%
c 8496
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4224
11.0%
n 4224
11.0%
C 48
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 34080
88.9%
Uppercase Letter 4272
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 8544
25.1%
c 8496
24.9%
h 4272
12.5%
k 4272
12.5%
d 4272
12.5%
n 4224
12.4%
Uppercase Letter
ValueCountFrequency (%)
U 4224
98.9%
C 48
 
1.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 38352
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 8544
22.3%
c 8496
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4224
11.0%
n 4224
11.0%
C 48
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 38352
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 8544
22.3%
c 8496
22.2%
h 4272
11.1%
k 4272
11.1%
d 4272
11.1%
U 4224
11.0%
n 4224
11.0%
C 48
 
0.1%
Distinct4
Distinct (%)0.1%
Missing1409
Missing (%)33.0%
Memory size33.5 KiB
Terapia Adjuvante
1422 
Terapia Neoadjuvante
1346 
Paliativo
 
70
Não fez quimioterapia
 
25

Length

Max length21
Median length20
Mean length18.249738
Min length9

Characters and Unicode

Total characters52249
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTerapia Adjuvante
2nd rowTerapia Adjuvante
3rd rowTerapia Neoadjuvante
4th rowTerapia Adjuvante
5th rowTerapia Neoadjuvante

Common Values

ValueCountFrequency (%)
Terapia Adjuvante 1422
33.3%
Terapia Neoadjuvante 1346
31.5%
Paliativo 70
 
1.6%
Não fez quimioterapia 25
 
0.6%
(Missing) 1409
33.0%

Length

2023-02-28T14:19:29.968099image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:30.616793image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
terapia 2768
48.7%
adjuvante 1422
25.0%
neoadjuvante 1346
23.7%
paliativo 70
 
1.2%
não 25
 
0.4%
fez 25
 
0.4%
quimioterapia 25
 
0.4%

Most occurring characters

ValueCountFrequency (%)
a 9840
18.8%
e 6932
13.3%
i 2983
 
5.7%
t 2863
 
5.5%
v 2838
 
5.4%
2818
 
5.4%
u 2793
 
5.3%
r 2793
 
5.3%
p 2793
 
5.3%
n 2768
 
5.3%
Other values (13) 12828
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 43800
83.8%
Uppercase Letter 5631
 
10.8%
Space Separator 2818
 
5.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 9840
22.5%
e 6932
15.8%
i 2983
 
6.8%
t 2863
 
6.5%
v 2838
 
6.5%
u 2793
 
6.4%
r 2793
 
6.4%
p 2793
 
6.4%
n 2768
 
6.3%
j 2768
 
6.3%
Other values (8) 4429
10.1%
Uppercase Letter
ValueCountFrequency (%)
T 2768
49.2%
A 1422
25.3%
N 1371
24.3%
P 70
 
1.2%
Space Separator
ValueCountFrequency (%)
2818
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 49431
94.6%
Common 2818
 
5.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 9840
19.9%
e 6932
14.0%
i 2983
 
6.0%
t 2863
 
5.8%
v 2838
 
5.7%
u 2793
 
5.7%
r 2793
 
5.7%
p 2793
 
5.7%
n 2768
 
5.6%
T 2768
 
5.6%
Other values (12) 10060
20.4%
Common
ValueCountFrequency (%)
2818
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52224
> 99.9%
None 25
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 9840
18.8%
e 6932
13.3%
i 2983
 
5.7%
t 2863
 
5.5%
v 2838
 
5.4%
2818
 
5.4%
u 2793
 
5.3%
r 2793
 
5.3%
p 2793
 
5.3%
n 2768
 
5.3%
Other values (12) 12803
24.5%
None
ValueCountFrequency (%)
ã 25
100.0%

hormonioterapia
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)33.3%
Missing4269
Missing (%)99.9%
Memory size33.5 KiB
Adjuvante

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters27
Distinct characters9
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAdjuvante
2nd rowAdjuvante
3rd rowAdjuvante

Common Values

ValueCountFrequency (%)
Adjuvante 3
 
0.1%
(Missing) 4269
99.9%

Length

2023-02-28T14:19:31.180970image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:31.743129image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
adjuvante 3
100.0%

Most occurring characters

ValueCountFrequency (%)
A 3
11.1%
d 3
11.1%
j 3
11.1%
u 3
11.1%
v 3
11.1%
a 3
11.1%
n 3
11.1%
t 3
11.1%
e 3
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
88.9%
Uppercase Letter 3
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
d 3
12.5%
j 3
12.5%
u 3
12.5%
v 3
12.5%
a 3
12.5%
n 3
12.5%
t 3
12.5%
e 3
12.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 3
11.1%
d 3
11.1%
j 3
11.1%
u 3
11.1%
v 3
11.1%
a 3
11.1%
n 3
11.1%
t 3
11.1%
e 3
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 3
11.1%
d 3
11.1%
j 3
11.1%
u 3
11.1%
v 3
11.1%
a 3
11.1%
n 3
11.1%
t 3
11.1%
e 3
11.1%

data_da_cirurgia
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct1653
Distinct (%)74.6%
Missing2056
Missing (%)48.1%
Memory size33.5 KiB
2016-02-18
 
5
2011-09-05
 
5
2013-08-25
 
4
2011-06-08
 
4
2012-08-07
 
4
Other values (1648)
2194 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters22160
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1206 ?
Unique (%)54.4%

Sample

1st row2009-09-04
2nd row2011-07-05
3rd row2011-05-21
4th row2010-10-05
5th row2009-05-07

Common Values

ValueCountFrequency (%)
2016-02-18 5
 
0.1%
2011-09-05 5
 
0.1%
2013-08-25 4
 
0.1%
2011-06-08 4
 
0.1%
2012-08-07 4
 
0.1%
2012-07-12 4
 
0.1%
2018-05-05 4
 
0.1%
2013-01-08 4
 
0.1%
2013-05-09 4
 
0.1%
2012-11-20 4
 
0.1%
Other values (1643) 2174
50.9%
(Missing) 2056
48.1%

Length

2023-02-28T14:19:31.938790image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2016-02-18 5
 
0.2%
2011-09-05 5
 
0.2%
2013-08-25 4
 
0.2%
2016-10-13 4
 
0.2%
2011-06-08 4
 
0.2%
2011-05-21 4
 
0.2%
2017-06-03 4
 
0.2%
2012-02-19 4
 
0.2%
2016-03-04 4
 
0.2%
2014-05-28 4
 
0.2%
Other values (1643) 2174
98.1%

Most occurring characters

ValueCountFrequency (%)
0 5085
22.9%
- 4432
20.0%
1 4216
19.0%
2 3949
17.8%
3 753
 
3.4%
6 734
 
3.3%
5 702
 
3.2%
7 666
 
3.0%
8 573
 
2.6%
4 563
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 17728
80.0%
Dash Punctuation 4432
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5085
28.7%
1 4216
23.8%
2 3949
22.3%
3 753
 
4.2%
6 734
 
4.1%
5 702
 
4.0%
7 666
 
3.8%
8 573
 
3.2%
4 563
 
3.2%
9 487
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 4432
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22160
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5085
22.9%
- 4432
20.0%
1 4216
19.0%
2 3949
17.8%
3 753
 
3.4%
6 734
 
3.3%
5 702
 
3.2%
7 666
 
3.0%
8 573
 
2.6%
4 563
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22160
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5085
22.9%
- 4432
20.0%
1 4216
19.0%
2 3949
17.8%
3 753
 
3.4%
6 734
 
3.3%
5 702
 
3.2%
7 666
 
3.0%
8 573
 
2.6%
4 563
 
2.5%

tipo_de_terapia_anti_her2_neoadjuvante
Categorical

IMBALANCE  MISSING 

Distinct2
Distinct (%)0.2%
Missing3138
Missing (%)73.5%
Memory size33.5 KiB
Trastuzumabe
1130 
Trastuzumabe + Pertuzumabe
 
4

Length

Max length26
Median length12
Mean length12.049383
Min length12

Characters and Unicode

Total characters13664
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTrastuzumabe
2nd rowTrastuzumabe
3rd rowTrastuzumabe
4th rowTrastuzumabe
5th rowTrastuzumabe

Common Values

ValueCountFrequency (%)
Trastuzumabe 1130
 
26.5%
Trastuzumabe + Pertuzumabe 4
 
0.1%
(Missing) 3138
73.5%

Length

2023-02-28T14:19:32.784182image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:32.989761image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
trastuzumabe 1134
99.3%
4
 
0.4%
pertuzumabe 4
 
0.4%

Most occurring characters

ValueCountFrequency (%)
u 2276
16.7%
a 2272
16.6%
e 1142
8.4%
r 1138
8.3%
t 1138
8.3%
z 1138
8.3%
m 1138
8.3%
b 1138
8.3%
T 1134
8.3%
s 1134
8.3%
Other values (3) 16
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12514
91.6%
Uppercase Letter 1138
 
8.3%
Space Separator 8
 
0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 2276
18.2%
a 2272
18.2%
e 1142
9.1%
r 1138
9.1%
t 1138
9.1%
z 1138
9.1%
m 1138
9.1%
b 1138
9.1%
s 1134
9.1%
Uppercase Letter
ValueCountFrequency (%)
T 1134
99.6%
P 4
 
0.4%
Space Separator
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13652
99.9%
Common 12
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 2276
16.7%
a 2272
16.6%
e 1142
8.4%
r 1138
8.3%
t 1138
8.3%
z 1138
8.3%
m 1138
8.3%
b 1138
8.3%
T 1134
8.3%
s 1134
8.3%
Common
ValueCountFrequency (%)
8
66.7%
+ 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13664
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
u 2276
16.7%
a 2272
16.6%
e 1142
8.4%
r 1138
8.3%
t 1138
8.3%
z 1138
8.3%
m 1138
8.3%
b 1138
8.3%
T 1134
8.3%
s 1134
8.3%
Other values (3) 16
 
0.1%

radioterapia
Categorical

CONSTANT  MISSING 

Distinct1
Distinct (%)< 0.1%
Missing1947
Missing (%)45.6%
Memory size33.5 KiB
Sim
2325 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters6975
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSim
2nd rowSim
3rd rowSim
4th rowSim
5th rowSim

Common Values

ValueCountFrequency (%)
Sim 2325
54.4%
(Missing) 1947
45.6%

Length

2023-02-28T14:19:33.131970image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:33.318273image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
sim 2325
100.0%

Most occurring characters

ValueCountFrequency (%)
S 2325
33.3%
i 2325
33.3%
m 2325
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4650
66.7%
Uppercase Letter 2325
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 2325
50.0%
m 2325
50.0%
Uppercase Letter
ValueCountFrequency (%)
S 2325
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6975
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 2325
33.3%
i 2325
33.3%
m 2325
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6975
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 2325
33.3%
i 2325
33.3%
m 2325
33.3%

data_de_inicio_do_tratamento_quimioterapia
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct1766
Distinct (%)62.6%
Missing1450
Missing (%)33.9%
Memory size33.5 KiB
2016-01-04
 
7
2017-09-04
 
6
2013-08-01
 
6
2011-11-25
 
6
2012-01-12
 
5
Other values (1761)
2792 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters28220
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1021 ?
Unique (%)36.2%

Sample

1st row2014-08-24
2nd row2011-09-08
3rd row2099-01-30
4th row2020-09-04
5th row2016-08-24

Common Values

ValueCountFrequency (%)
2016-01-04 7
 
0.2%
2017-09-04 6
 
0.1%
2013-08-01 6
 
0.1%
2011-11-25 6
 
0.1%
2012-01-12 5
 
0.1%
2011-11-27 5
 
0.1%
2013-11-14 5
 
0.1%
2016-09-02 5
 
0.1%
2017-05-29 5
 
0.1%
2016-03-15 5
 
0.1%
Other values (1756) 2767
64.8%
(Missing) 1450
33.9%

Length

2023-02-28T14:19:33.517193image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2016-01-04 7
 
0.2%
2013-08-01 6
 
0.2%
2011-11-25 6
 
0.2%
2017-09-04 6
 
0.2%
2017-05-29 5
 
0.2%
2015-06-08 5
 
0.2%
2016-03-15 5
 
0.2%
2017-07-25 5
 
0.2%
2016-09-02 5
 
0.2%
2013-11-14 5
 
0.2%
Other values (1756) 2767
98.1%

Most occurring characters

ValueCountFrequency (%)
0 6291
22.3%
- 5644
20.0%
1 5547
19.7%
2 4977
17.6%
3 969
 
3.4%
7 950
 
3.4%
6 935
 
3.3%
5 896
 
3.2%
4 774
 
2.7%
8 721
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 22576
80.0%
Dash Punctuation 5644
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 6291
27.9%
1 5547
24.6%
2 4977
22.0%
3 969
 
4.3%
7 950
 
4.2%
6 935
 
4.1%
5 896
 
4.0%
4 774
 
3.4%
8 721
 
3.2%
9 516
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 5644
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28220
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 6291
22.3%
- 5644
20.0%
1 5547
19.7%
2 4977
17.6%
3 969
 
3.4%
7 950
 
3.4%
6 935
 
3.3%
5 896
 
3.2%
4 774
 
2.7%
8 721
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28220
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 6291
22.3%
- 5644
20.0%
1 5547
19.7%
2 4977
17.6%
3 969
 
3.4%
7 950
 
3.4%
6 935
 
3.3%
5 896
 
3.2%
4 774
 
2.7%
8 721
 
2.6%
Distinct3
Distinct (%)25.0%
Missing4260
Missing (%)99.7%
Memory size33.5 KiB
Inibidor de aromatase isolado
Switch: tamoxifeno seguido de IA
Tamoxifeno isolado

Length

Max length32
Median length29
Mean length27.25
Min length18

Characters and Unicode

Total characters327
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowInibidor de aromatase isolado
2nd rowSwitch: tamoxifeno seguido de IA
3rd rowTamoxifeno isolado
4th rowSwitch: tamoxifeno seguido de IA
5th rowTamoxifeno isolado

Common Values

ValueCountFrequency (%)
Inibidor de aromatase isolado 5
 
0.1%
Switch: tamoxifeno seguido de IA 4
 
0.1%
Tamoxifeno isolado 3
 
0.1%
(Missing) 4260
99.7%

Length

2023-02-28T14:19:33.748694image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:33.992248image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
de 9
19.6%
isolado 8
17.4%
tamoxifeno 7
15.2%
inibidor 5
10.9%
aromatase 5
10.9%
switch 4
8.7%
seguido 4
8.7%
ia 4
8.7%

Most occurring characters

ValueCountFrequency (%)
o 44
13.5%
34
10.4%
i 33
10.1%
a 30
 
9.2%
d 26
 
8.0%
e 25
 
7.6%
s 17
 
5.2%
t 13
 
4.0%
n 12
 
3.7%
m 12
 
3.7%
Other values (15) 81
24.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 269
82.3%
Space Separator 34
 
10.4%
Uppercase Letter 20
 
6.1%
Other Punctuation 4
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 44
16.4%
i 33
12.3%
a 30
11.2%
d 26
9.7%
e 25
9.3%
s 17
 
6.3%
t 13
 
4.8%
n 12
 
4.5%
m 12
 
4.5%
r 10
 
3.7%
Other values (9) 47
17.5%
Uppercase Letter
ValueCountFrequency (%)
I 9
45.0%
S 4
20.0%
A 4
20.0%
T 3
 
15.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Other Punctuation
ValueCountFrequency (%)
: 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 289
88.4%
Common 38
 
11.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 44
15.2%
i 33
11.4%
a 30
10.4%
d 26
 
9.0%
e 25
 
8.7%
s 17
 
5.9%
t 13
 
4.5%
n 12
 
4.2%
m 12
 
4.2%
r 10
 
3.5%
Other values (13) 67
23.2%
Common
ValueCountFrequency (%)
34
89.5%
: 4
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 327
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 44
13.5%
34
10.4%
i 33
10.1%
a 30
 
9.2%
d 26
 
8.0%
e 25
 
7.6%
s 17
 
5.2%
t 13
 
4.0%
n 12
 
3.7%
m 12
 
3.7%
Other values (15) 81
24.8%

data_do_inicio_hormonioterapia_adjuvante
Categorical

MISSING  UNIFORM 

Distinct2
Distinct (%)100.0%
Missing4270
Missing (%)> 99.9%
Memory size33.5 KiB
2013-01-07
2021-06-24

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters20
Distinct characters8
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row2013-01-07
2nd row2021-06-24

Common Values

ValueCountFrequency (%)
2013-01-07 1
 
< 0.1%
2021-06-24 1
 
< 0.1%
(Missing) 4270
> 99.9%

Length

2023-02-28T14:19:34.170393image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-02-28T14:19:34.383826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
ValueCountFrequency (%)
2013-01-07 1
50.0%
2021-06-24 1
50.0%

Most occurring characters

ValueCountFrequency (%)
0 5
25.0%
2 4
20.0%
- 4
20.0%
1 3
15.0%
3 1
 
5.0%
7 1
 
5.0%
6 1
 
5.0%
4 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
80.0%
Dash Punctuation 4
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5
31.2%
2 4
25.0%
1 3
18.8%
3 1
 
6.2%
7 1
 
6.2%
6 1
 
6.2%
4 1
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5
25.0%
2 4
20.0%
- 4
20.0%
1 3
15.0%
3 1
 
5.0%
7 1
 
5.0%
6 1
 
5.0%
4 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5
25.0%
2 4
20.0%
- 4
20.0%
1 3
15.0%
3 1
 
5.0%
7 1
 
5.0%
6 1
 
5.0%
4 1
 
5.0%

data_de_inicio_da_radioterapia
Categorical

HIGH CARDINALITY  MISSING  UNIFORM 

Distinct1708
Distinct (%)73.5%
Missing1949
Missing (%)45.6%
Memory size33.5 KiB
2016-06-03
 
5
2016-05-05
 
5
2013-08-04
 
5
2014-07-20
 
4
2016-11-06
 
4
Other values (1703)
2300 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters23230
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1235 ?
Unique (%)53.2%

Sample

1st row2011-11-23
2nd row2010-04-27
3rd row2011-10-11
4th row2010-12-16
5th row2011-07-27

Common Values

ValueCountFrequency (%)
2016-06-03 5
 
0.1%
2016-05-05 5
 
0.1%
2013-08-04 5
 
0.1%
2014-07-20 4
 
0.1%
2016-11-06 4
 
0.1%
2018-09-27 4
 
0.1%
2018-09-21 4
 
0.1%
2012-05-26 4
 
0.1%
2012-03-01 4
 
0.1%
2013-01-02 4
 
0.1%
Other values (1698) 2280
53.4%
(Missing) 1949
45.6%

Length

2023-02-28T14:19:34.551460image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2016-06-03 5
 
0.2%
2013-08-04 5
 
0.2%
2016-05-05 5
 
0.2%
2016-09-20 4
 
0.2%
2013-10-19 4
 
0.2%
2016-12-15 4
 
0.2%
2013-06-17 4
 
0.2%
2016-05-24 4
 
0.2%
2016-05-15 4
 
0.2%
2012-04-26 4
 
0.2%
Other values (1698) 2280
98.1%

Most occurring characters

ValueCountFrequency (%)
0 5286
22.8%
- 4646
20.0%
1 4383
18.9%
2 4158
17.9%
3 792
 
3.4%
6 754
 
3.2%
5 720
 
3.1%
8 711
 
3.1%
7 701
 
3.0%
4 599
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18584
80.0%
Dash Punctuation 4646
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5286
28.4%
1 4383
23.6%
2 4158
22.4%
3 792
 
4.3%
6 754
 
4.1%
5 720
 
3.9%
8 711
 
3.8%
7 701
 
3.8%
4 599
 
3.2%
9 480
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 4646
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5286
22.8%
- 4646
20.0%
1 4383
18.9%
2 4158
17.9%
3 792
 
3.4%
6 754
 
3.2%
5 720
 
3.1%
8 711
 
3.1%
7 701
 
3.0%
4 599
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5286
22.8%
- 4646
20.0%
1 4383
18.9%
2 4158
17.9%
3 792
 
3.4%
6 754
 
3.2%
5 720
 
3.1%
8 711
 
3.1%
7 701
 
3.0%
4 599
 
2.6%

Interactions

2023-02-28T14:19:03.360871image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:51.904918image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:54.481477image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:56.506838image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:58.623538image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:59.913139image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:01.266982image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:03.650203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:52.097223image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:54.789589image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:56.798504image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:58.827660image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:00.110807image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:01.463239image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:03.874259image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:52.946077image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:55.098203image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:57.125945image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:59.022799image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:00.313324image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:01.647893image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:04.088377image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:53.218039image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:55.379177image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:57.422450image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:59.207551image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:00.518476image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:01.832066image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:04.351120image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:53.515739image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:55.590981image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:57.673574image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:59.389281image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:00.694518image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:01.998361image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:04.541425image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:53.854470image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:55.910364image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:58.016070image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:59.556296image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:00.894265image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:02.192681image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:04.727914image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:54.161657image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:56.195889image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:58.321295image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:18:59.745064image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:01.083319image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
2023-02-28T14:19:02.369570image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/

Missing values

2023-02-28T14:19:05.155922image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
A simple visualization of nullity by column.
2023-02-28T14:19:06.594945image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-02-28T14:19:07.643826image/svg+xmlMatplotlib v3.5.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

record_idrepeat_instrumentrepeat_instanceescolaridadeidade_do_paciente_ao_primeiro_diagnosticosexoraca_declarada_biobancouf_de_nascimento_do_pacienteuf_de_residencia_do_pacientedata_da_ultima_informacao_sobre_o_pacienteultima_informacao_do_pacientetempo_de_seguimento_em_dias_desde_o_ultimo_tumor_no_caso_de_tumores_multiplos_dt_pcija_ficou_gravidaquantas_vezes_ficou_gravidanumero_de_partosidade_na_primeira_gestacaoabortouamamentou_na_primeira_gestacaopor_quanto_tempo_amamentouhistoria_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_naohistoria_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_1o_grau_apenas_1_casohistoria_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_1o_grau_mais_de_1_casohistoria_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_2o_grau_apenas_1_casohistoria_familiar_de_cancer_relacionado_a_sindrome_de_cancer_de_mama_e_ovario_hereditaria_choice_sim_2o_grau_mais_de_1_casoidade_da_primeira_mentruacaofaz_uso_de_metodos_contraceptivoqual_metodo_choice_pilula_anticoncepcionalqual_metodo_choice_diuqual_metodo_choice_camisinhaqual_metodo_choice_outrosqual_metodo_choice_nao_informouja_fez_uso_de_drogasatividade_fisicaconsumo_de_tabacoconsumo_de_alcoolpossui_historico_familiar_de_cancergrau_de_parentesco_de_familiar_com_cancer_choice_primeiro_pais_irmaos_filhosgrau_de_parentesco_de_familiar_com_cancer_choice_segundo_avos_tios_e_netosgrau_de_parentesco_de_familiar_com_cancer_choice_terceiro_bisavos_tio_avos_primos_sobrinhosregime_de_tratamentohormonioterapiadata_da_cirurgiatipo_de_terapia_anti_her2_neoadjuvanteradioterapiadata_de_inicio_do_tratamento_quimioterapiaesquema_de_hormonioterapiadata_do_inicio_hormonioterapia_adjuvantedata_de_inicio_da_radioterapia
0302NaNNaNENS. FUNDAMENTAL INCOMPLETO51.0FemininoNaNNaNNaN2014-04-26Obito por câncer2225.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedNaNNaNNaNTrastuzumabeNaNNaNInibidor de aromatase isoladoNaNNaN
1710NaNNaNENSINO MÉDIO58.0FemininoNaNNaNNaN2016-11-17Vivo, SOE3294.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedTerapia AdjuvanteNaN2009-09-04NaNNaN2014-08-24NaNNaNNaN
2752NaNNaNENS. FUNDAMENTAL INCOMPLETO56.0FemininoNaNNaNNaN2019-05-02Vivo, SOE4153.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNNaNNaNNaNNaN
31367NaNNaNENS. FUNDAMENTAL INCOMPLETO63.0FemininoNaNNaNNaN2011-09-29Obito por câncer1331.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedNaNNaN2011-07-05NaNNaNNaNNaNNaNNaN
41589NaNNaNENS. FUNDAMENTAL COMPLETO42.0FemininoNaNNaNNaN2017-05-24Vivo, SOE3290.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNNaNNaNNaNNaN
51705NaNNaNENS. FUNDAMENTAL INCOMPLETO43.0FemininoNaNNaNNaN2013-06-11Obito por câncer2224.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedTerapia AdjuvanteNaN2011-05-21NaNSim2011-09-08NaNNaN2011-11-23
61843NaNNaNIGNORADA52.0FemininoNaNNaNNaN2009-01-25Vivo, com câncer182.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedNaNNaN2010-10-05TrastuzumabeNaNNaNNaNNaNNaN
71873NaNNaNIGNORADA40.0FemininoNaNNaNNaN2017-07-08Vivo, SOE3234.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedNaNNaNNaNTrastuzumabeNaNNaNSwitch: tamoxifeno seguido de IANaNNaN
81898NaNNaNENS. FUNDAMENTAL COMPLETO60.0FemininoNaNNaNNaN2009-08-22Obito por câncer428.0NaNNaNNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNUncheckedUncheckedUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNUncheckedUncheckedUncheckedNaNNaNNaNNaNNaNNaNNaNNaNNaN
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